# Higgsfield Prompt > Use when building, writing, refining, or structuring a Higgsfield AI prompt. Covers the MCSLA formula, prompt structure, narrative vs. timestamped formats, and how to write for both text-to-video and image-to-video workflows. - **Type:** Skill - **Install:** `agentstack add skill-osidemedia-higgsfield-ai-prompt-skill-higgsfield-prompt` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [OSideMedia](https://agentstack.voostack.com/s/osidemedia) - **Installs:** 0 - **Category:** [Content & Media](https://agentstack.voostack.com/c/content-and-media) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [OSideMedia](https://github.com/OSideMedia) - **Source:** https://github.com/OSideMedia/higgsfield-ai-prompt-skill/tree/main/skills/higgsfield-prompt - **Website:** https://higgsfield.ai ## Install ```sh agentstack add skill-osidemedia-higgsfield-ai-prompt-skill-higgsfield-prompt ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Higgsfield Prompt Engineering ## QUICK FACTS *Generated-checked block (build_index.py verifies anchors). Read the linked sections for full context — these lines are routing aids, not the rules themselves.* - MCSLA = Model, Camera, Subject, Look, Action — the five layers of every prompt [→](#the-mcsla-formula) - I2V: describe ONLY what moves or changes, never what's already in the image [→](#image-to-video-i2v) - Keep prompts under 200 words; Cinema Studio has a hard 512-character cap [→](#high-performing-prompt-patterns) - 1 primary action per clip, 1–2 secondary max; Fast Motion Trick: render in Slow Mo, speed up in post [→](#one-action-per-scene) - Never leave a generic emotion ("sad"/"angry") in a prompt — decompose into muscle movements, breath, eyes, skin [→](#generic-emotion-decomposition-which-kind-of-x) - Soul ID / recurring characters: split every prompt into Identity Block + Motion Block — never mix them [→](#identity-vs-motion-separation-rule) - Conflict order when sub-skills disagree: explicit user direction > scene archetype > emotion-sync [→](#conflict-resolution-between-sub-skills) - Aspect ratio is a per-model enum set in the UI/header, never in the prompt body — verify via `../../specs/model-specs.yaml` [→](#common-prompt-mistakes) - Never combine Dolly In + Dolly Out in one shot; @ Elements for static scenes, plain text for action [→](#common-prompt-mistakes) - Iterate by changing exactly ONE variable per regeneration [→](#the-iteration-rule-change-one-variable-at-a-time) - 6-Pass Diagnostic order: Subject → Action → Camera → Style → Audio → Output; most failures land on Pass 1–2 [→](#when-you-dont-know-whats-wrong-yet-the-6-pass-diagnostic-sequence) - Seedance: short prompts (30–100 words) win; Subject + Action must sit in the first 20–30 words [→](#the-directors-formula-mcsla-mapping) - Genre length targets: Product 30–50w, Lifestyle 40–60w, Drama 60–100w, Music Video 50–80w, Anime 50–90w [→](#genre-router-prompt-length-lead-with-targets) - Kill slop words (beautiful, stunning, epic, amazing) — replace with concrete visuals/physics [→](#anti-slop-vocabulary) - Seedance/CS 3.0 has NO negative-prompt syntax — phrase as positive constraints [→](#no-negative-prompts) - Dialogue cap: ~25–30 spoken words fit in 15 seconds — keep the power-shift line, convert the rest to behavior [→](#dialogue-archetypes) - Engine limits: ≤3 characters tracked across cuts; exit-frame = gone; off-screen = nonexistent; avoid reflections [→](#character-spatial-rules) - Every cut must change BOTH shot size AND camera character [→](#double-contrast-cut-rule-mandatory) - Age-blind rule: never boy/girl/child/kid/young/teen/little — describe by role, clothing, action [→](#age-blind-character-rule) - Scenes start already in progress unless the user says "starts with…" or "ends with…" [→](#default-in-medias-res) ## The MCSLA Formula Every high-performing Higgsfield prompt is built on five layers. Think of it as the cinematographer's checklist — fill in each layer and the model has everything it needs. | Letter | Element | Description | Example | |--------|---------|-------------|---------| | **M** | Model | Which generation engine | "Use Kling 2.6" | | **C** | Camera | Named camera control | "FPV Drone shot weaving through the alley" | | **S** | Subject | Who/what + appearance | "A woman in a sand-colored suit, sharp eyes" | | **L** | Look | Style + color + lighting | "Cinematic, golden hour, anamorphic flare" | | **A** | Action | What happens in the scene | "She turns slowly, wind lifting her coat" | --- ## Prompt Types ### Text-to-Video (T2V) Start from nothing — describe the entire scene from scratch. Best for: establishing scenes, abstract concepts, environments without a specific character. ``` [Subject + appearance]. [Environment — location, time, weather, atmosphere]. [Action — what happens and how]. [Camera — named control]. [Look — style + color grade]. ``` **Example:** ``` A lone astronaut stands on the surface of a red desert planet, helmet visor reflecting twin moons rising on the horizon. Dust spirals slowly in the thin atmosphere. She turns to face the camera, gloved hand raised in a slow salute. Camera: slow Crane Up revealing the vast emptiness behind her. Style: Cinematic, desaturated orange and deep blue, 2.35:1 anamorphic. ``` --- ### Image-to-Video (I2V) Animate a provided still image. The image defines the starting frame. Best for: character consistency, product shots, portrait animation, storyboard bring-to-life. ``` [Reference the input image as the first frame]. [Describe what should move, change, or animate — not what is already visible]. [Camera — named control]. [Style/atmosphere cues]. ``` **Example:** ``` Starting from the provided image as the first frame. The woman's hair lifts gently in the wind. She blinks slowly and turns her gaze slightly to the left, a faint smile forming. Camera: subtle Dolly In toward her face. Style: Cinematic, warm afternoon light, shallow depth of field. ``` **Key rule for I2V:** Do NOT re-describe what is already in the image. Only describe what should *change* or *animate*. Over-describing the static elements confuses the model. This applies equally to @ Image references in Seedance/Cinema Studio 3.0 — describe ONLY motion and camera movement, never what's already visible. --- ## Narrative Structure ### Fluid Narrative (preferred for most use cases) Write the scene as continuous action. No timestamps. Most natural for Higgsfield. ``` A detective pushes open the door to the rain-soaked rooftop, coat whipping in the wind. She steps to the edge and looks down at the city below — a thousand lights blurring through the downpour. Camera dollies slowly behind her, then cranes up to reveal the skyline. Cinematic style, cold blue tones, 16:9. ``` ### Timestamped (use only for precise multi-beat sequences) Only use when exact timing of separate actions matters — e.g., a transformation, a multi-phase action sequence, or a beat-synced music video. Maps to Cinema Studio 3.0's Custom multi-shot mode. ``` 0–3s: Wide establishing shot. The fighter stands alone in the ring, chest heaving. 3–6s: Crash Zoom In on his face. Sweat on his brow, jaw clenched. 6–10s: 360 Orbit as he raises his fists. Crowd noise rises. ``` --- ## High-Performing Prompt Patterns > **The #1 mistake in video prompting**: over-describing appearance and under-describing > behavior. Give your subject something to DO. Give them an internal state that creates > visible behavior. A verb that describes motion or intention is more important than > adjectives. **Specificity beats generality:** - ❌ "the camera moves dramatically" - ✅ "camera Dolly Zoom In — subject stays the same size as the background rushes forward" **Active verbs carry the scene:** - ❌ "a woman is in an alley" - ✅ "a woman darts through a rain-soaked alley, coat flapping, boots splashing" **Name the camera control:** Higgsfield understands its own preset names. Always use them explicitly. - ❌ "the camera slowly circles" - ✅ "360 Orbit around the subject" **Lead with subject, end with style:** Subject → Action → Camera → Style is the most reliable order. **Keep it under 200 words:** Focused prompts outperform exhaustive ones. One clear intention > ten vague details. **Cinema Studio: Keep it under 512 characters:** Cinema Studio has a hard 512-character limit on prompts (both 2.5 and 3.0). - **2.5:** @ Element chips consume ~80–100 hidden characters each. With 2 @ tags, keep visible text under ~250 chars. - **3.0:** @ references (images/video/audio) are media attachments, not inline metadata — they consume less hidden space. Keep visible text under ~350–400 chars with references, ~450–500 without. See the Cinema Studio skill for full character budget details. --- ## The Pre-Prompt Checklist Before writing any prompt, answer these five questions. Vague prompts like "give me something cinematic" tell the AI nothing. | Question | What to specify | |----------|----------------| | **Who?** | Subject + appearance (e.g. "a man in a leather jacket") | | **Where?** | Environment + atmosphere (e.g. "in a narrow aircraft galley, cold blue light") | | **What's happening?** | 1 primary action (e.g. "punches his opponent") | | **Camera movement?** | Named preset (e.g. "Handheld") or Cinema Studio Director Panel | | **Mood/Genre?** | Style + color grade, or Cinema Studio genre selection | --- ## One Action Per Scene AI models can replicate real-life physics — but only so much at once. Asking for multiple complex actions in one clip overwhelms the model. **Rule:** 1 primary action per clip, with 1–2 secondary actions max. Break complex sequences into separate shots and stitch them in a video editor, or use Multi-Shot Manual mode to prompt each scene separately. **Fast Motion Trick:** If fast motion keeps morphing or breaking, generate the scene in Slow Mo first, then speed it up in post (CapCut, Premiere, DaVinci). The model renders cleaner physics in slow motion. --- ## Generic-Emotion Decomposition — Which kind of X? Never leave a generic emotion in a prompt. "Sad" / "angry" / "surprised" / "scared" / "thoughtful" / "in love" — each is at least three or four distinct physical realizations, and the model renders a different version depending on which one your prompt invites. A prompt that says only "she looks surprised" produces a different shot every regeneration and degrades adherence across batches. The rule: decompose the generic emotion into specific muscle movements, breath, eyes, and skin. If you can't decompose confidently, ask the user to choose a variant. Clarification template — offer when the script or user supplies a generic emotion you cannot decompose without inventing detail: > Which kind of surprise? > (a) Light positive — eyebrows lift, lips part softly, slow inhale > through the nose, no other movement. > (b) Shock — sharp inhale through the mouth, eyes widen, body > freezes in place, hand involuntarily lifts to chest. > (c) Disbelief — slow blink, head tilts a fraction, lips press > together, only one eyebrow lifts. > (d) Surprise-with-joy — eye light shifts (catchlight reads), > smile builds gradually, shoulders relax. Same shape applies to any generic adjective — "tense" / "sad" / "angry" / "scared" / "thoughtful" / "in love" each decomposes into 3-5 distinct physical realizations. The decomposed prompt produces a performance; the generic prompt produces AI-video. > **Preset library alternative.** For named micro-expression presets > that drop into a prompt without first-principles decomposition, > see `../higgsfield-soul/SKILL.md` § Micro-Expressions. The catalog > covers most common emotional registers with locked physical > descriptors. Use the decompose-from-first-principles rule above > when no preset matches; use the preset library when one does. ### Layered emotion states Single-axis decomposition (above) names one register: angry / sad / surprised. **Layered emotion** names a composite state where two registers stack — *anxious determination*, *tired tenderness*, *bitter amusement*, *cornered calculation*. Production-team practice finds the model renders layered states better than single registers when the layering is described as *one channel modulating another*: the dominant state plus the underlying state plus the visible tell. - **Anxious determination** — set jaw + locked gaze (determination) with shallow chest breath and a single hand at the side flexing open-closed (anxiety underneath). - **Tired tenderness** — soft micro-smile + half-closed eyes (tenderness) with the body weight settled, slow blink interval (tiredness underneath). - **Bitter amusement** — one-sided smirk + eye-shine (amusement) with no smile crinkles at the eye corners (bitterness underneath). Compose layered states by stacking decomposed physical realizations from the single-axis catalog. The dominant state goes in the face; the underlying state goes in breath, posture, and hand-state; the visible tell sits in the eyes. For finer control, layer a **tiny detail** on top of an existing emotional cue: `Roco is very upset, and his lower lip trembles`. The base emotion gets the broad performance; the tiny detail gives the model a specific physical cue to render. Production-team discipline holds that the model renders the simple-emotion-plus- tiny-detail compound better than either an over-decomposed prompt or a too-generic one. --- ## Identity vs. Motion Separation Rule When a prompt involves Soul ID or any character who must stay consistent across shots, **always split the output into two clearly labeled blocks**: ### Identity Block — Static visual descriptors ONLY - Face features, skin tone, body type, distinguishing marks - Clothing, accessories, color palette - NO motion, NO camera, NO temporal language ### Motion Block — Temporal and camera ONLY - Camera movement, action choreography, speed - Environmental motion, atmospheric changes - NO character appearance repetition **Bad (mixed) — identity drifts:** ``` A woman with sharp cheekbones and auburn hair in a blue trench coat runs through a rain-soaked alley, her coat flapping, sharp cheekbones catching the neon light, camera chasing her at full speed, her auburn hair streaming behind her. ``` **Good (separated) — identity stays locked:** **Identity Block:** ``` The Soul ID character — sharp cheekbones, auburn hair shoulder-length, wearing a blue trench coat with silver buttons, lean athletic build. ``` **Motion Block:** ``` She runs through a rain-soaked alley, coat flapping behind her. Camera: Action Run — low behind, matching pace. Neon reflections streak across wet concrete. Style: Cinematic, cold blue shadows, warm neon accents. 16:9. ``` **When to apply this rule:** - Always when Soul ID is active - Always in multi-shot sequences where the same character appears - Always when camera movement is involved alongside a character - In Cinema Studio, identity goes in the @ Element definition; motion goes in the prompt > **Camera matches emotion, not just identity.** The Motion Block describes WHAT > the character does and HOW the camera moves. The *quality* of the camera motion > — jittery handheld for anger, smooth handheld breathing for calm, static + slow > push for revelation — should track the focal character's emotional state. See > `../higgsfield-camera/SKILL.md` § Camera-Emotion Sync for the 6-emotion movement > map and the emotional-arcs-within-a-shot pattern. For decomposing the underlying > generic emotion before picking a camera prescription, see § Generic-Emotion > Decomposition above. --- ## Conflict resolution between sub-skills Sub-skills can legitimately nominate different things for the same shot. `higgsfield-camera § Camera-Emotion Sync` nominates handheld-slow-low for sadness; `higgsfield-prompt § Scene Archetype Router` permits locked dolly-in for the Atmosphere archetype where mood-is-the-content. When two sub-skills nominate different camera moves (or motion presets, or style registers) for the same scene, resolve in this order: 1. **Explicit user direction wins.** If the user said "slow push-in," that's the camera move. The agent's job is to make that direction work with the rest of the structure, not to override it. 2. **Scene archetype next.** If the user did not specify, pick the archetype-recommended move (Atmosphere → static / slow push-in / locked-off; Action → handheld / whip-pan / FPV; Dialogue → shoulder-coverage / push-in on emotion). 3. **Emotion-sync register last.** Camera-Emotion Sync nominations are the default tiebreaker when archetype is unclear. When the resolution is non-obvious, surface it. Tell the user which sub-skill nominated what and why you picked one over the other — this is meta-correct behavior and lets the user override. Silent picking is the failure mode; transparent picking is the discipline. --- ## Common Prompt Mistakes | Mistake | Fix | … ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [OSideMedia](https://github.com/OSideMedia) - **Source:** [OSideMedia/higgsfield-ai-prompt-skill](https://github.com/OSideMedia/higgsfield-ai-prompt-skill) - **License:** MIT - **Homepage:** https://higgsfield.ai Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-osidemedia-higgsfield-ai-prompt-skill-higgsfield-prompt - Seller: https://agentstack.voostack.com/s/osidemedia - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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